--- license: apache-2.0 base_model: facebook/bart-base tags: - generated_from_keras_callback model-index: - name: pijarcandra22/NMTBaliIndoBART results: [] --- # pijarcandra22/NMTBaliIndoBART This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 5.4797 - Validation Loss: 5.9510 - Epoch: 235 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 0.02, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} - training_precision: float32 ### Training results | Train Loss | Validation Loss | Epoch | |:----------:|:---------------:|:-----:| | 9.3368 | 5.6757 | 0 | | 5.5627 | 5.5987 | 1 | | 5.5311 | 5.5419 | 2 | | 5.5152 | 5.5201 | 3 | | 5.5005 | 5.6477 | 4 | | 5.4704 | 5.5914 | 5 | | 5.4610 | 6.0922 | 6 | | 5.4584 | 5.7137 | 7 | | 5.4528 | 5.8658 | 8 | | 5.4820 | 5.5628 | 9 | | 5.4874 | 5.5309 | 10 | | 5.4917 | 5.7595 | 11 | | 5.4898 | 5.7333 | 12 | | 5.4833 | 5.6789 | 13 | | 5.4767 | 5.9588 | 14 | | 5.4883 | 5.9895 | 15 | | 5.4694 | 6.0100 | 16 | | 5.4663 | 6.0316 | 17 | | 5.4602 | 5.9233 | 18 | | 5.4576 | 6.0051 | 19 | | 5.4559 | 5.9966 | 20 | | 5.4651 | 6.0025 | 21 | | 5.4660 | 6.0160 | 22 | | 5.4626 | 5.8324 | 23 | | 5.4647 | 5.8383 | 24 | | 5.4695 | 6.0272 | 25 | | 5.4614 | 6.0724 | 26 | | 5.4623 | 5.9454 | 27 | | 5.4678 | 6.0196 | 28 | | 5.4860 | 5.5949 | 29 | | 5.4851 | 5.8838 | 30 | | 5.4666 | 5.8506 | 31 | | 5.4715 | 6.0391 | 32 | | 5.4630 | 6.0870 | 33 | | 5.4646 | 6.2195 | 34 | | 5.4574 | 5.9696 | 35 | | 5.4564 | 5.8970 | 36 | | 5.4570 | 5.9522 | 37 | | 5.4559 | 6.1518 | 38 | | 5.4584 | 6.1860 | 39 | | 5.4732 | 6.1168 | 40 | | 5.4625 | 6.1588 | 41 | | 5.4601 | 5.9868 | 42 | | 5.4645 | 5.9606 | 43 | | 5.4664 | 6.1495 | 44 | | 5.4698 | 6.0152 | 45 | | 5.4666 | 6.2713 | 46 | | 5.4557 | 6.2708 | 47 | | 5.4557 | 6.0003 | 48 | | 5.4693 | 5.9321 | 49 | | 5.4928 | 5.8971 | 50 | | 5.5032 | 6.0766 | 51 | | 5.4749 | 5.8919 | 52 | | 5.4689 | 5.9853 | 53 | | 5.4665 | 5.9329 | 54 | | 5.4574 | 5.9770 | 55 | | 5.4686 | 6.1022 | 56 | | 5.4727 | 5.8973 | 57 | | 5.4692 | 5.9633 | 58 | | 5.4608 | 6.0480 | 59 | | 5.4613 | 5.9596 | 60 | | 5.4607 | 6.1158 | 61 | | 5.4531 | 6.0617 | 62 | | 5.4610 | 6.0375 | 63 | | 5.4631 | 6.1184 | 64 | | 5.4627 | 6.0465 | 65 | | 5.4685 | 6.0011 | 66 | | 5.4642 | 6.0828 | 67 | | 5.4577 | 6.0883 | 68 | | 5.4615 | 5.9523 | 69 | | 5.4673 | 5.7216 | 70 | | 5.4724 | 6.0274 | 71 | | 5.4601 | 6.0344 | 72 | | 5.4640 | 5.9661 | 73 | | 5.4590 | 6.0013 | 74 | | 5.4622 | 6.0172 | 75 | | 5.4666 | 5.8407 | 76 | | 5.4669 | 6.0261 | 77 | | 5.4859 | 5.9295 | 78 | | 5.5042 | 6.1254 | 79 | | 5.4845 | 5.8930 | 80 | | 5.5001 | 5.8867 | 81 | | 5.4923 | 5.9480 | 82 | | 5.4909 | 6.0475 | 83 | | 5.4780 | 5.9289 | 84 | | 5.4867 | 5.8134 | 85 | | 5.4877 | 6.0032 | 86 | | 5.4806 | 6.0884 | 87 | | 5.4784 | 6.0567 | 88 | | 5.4830 | 5.9790 | 89 | | 5.4894 | 5.8919 | 90 | | 5.4890 | 5.9626 | 91 | | 5.4774 | 6.0267 | 92 | | 5.5033 | 6.1150 | 93 | | 5.4765 | 5.9776 | 94 | | 5.4657 | 6.1395 | 95 | | 5.4720 | 5.9938 | 96 | | 5.4748 | 5.9656 | 97 | | 5.4701 | 6.0163 | 98 | | 5.4718 | 6.1462 | 99 | | 5.4672 | 6.0804 | 100 | | 5.4775 | 6.1055 | 101 | | 5.4775 | 6.0936 | 102 | | 5.4673 | 5.9839 | 103 | | 5.4691 | 5.8972 | 104 | | 5.4694 | 5.8271 | 105 | | 5.5106 | 5.5305 | 106 | | 5.5135 | 5.8806 | 107 | | 5.4786 | 6.1380 | 108 | | 5.4770 | 5.9899 | 109 | | 5.4709 | 6.1072 | 110 | | 5.4701 | 5.9356 | 111 | | 5.4636 | 5.8304 | 112 | | 5.4670 | 6.0451 | 113 | | 5.4598 | 6.0311 | 114 | | 5.4731 | 5.9862 | 115 | | 5.4798 | 5.9589 | 116 | | 5.4674 | 5.9356 | 117 | | 5.4634 | 6.0088 | 118 | | 5.4709 | 5.9534 | 119 | | 5.4891 | 5.9995 | 120 | | 5.4737 | 5.8611 | 121 | | 5.4725 | 6.0112 | 122 | | 5.4835 | 5.6280 | 123 | | 5.5217 | 5.6917 | 124 | | 5.4821 | 5.9458 | 125 | | 5.4898 | 5.7593 | 126 | | 5.4866 | 5.9110 | 127 | | 5.4744 | 5.9463 | 128 | | 5.4673 | 6.0359 | 129 | | 5.4838 | 6.0166 | 130 | | 5.4864 | 6.0046 | 131 | | 5.4896 | 5.9479 | 132 | | 5.4722 | 6.0699 | 133 | | 5.4627 | 6.0684 | 134 | | 5.4690 | 6.0577 | 135 | | 5.4666 | 6.1473 | 136 | | 5.4655 | 6.0441 | 137 | | 5.4665 | 5.9313 | 138 | | 5.4588 | 6.1375 | 139 | | 5.4575 | 6.1655 | 140 | | 5.4609 | 5.9701 | 141 | | 5.4666 | 6.0677 | 142 | | 5.4672 | 6.1272 | 143 | | 5.4776 | 6.2186 | 144 | | 5.4769 | 5.9815 | 145 | | 5.4666 | 6.0674 | 146 | | 5.4670 | 6.0282 | 147 | | 5.4868 | 5.7416 | 148 | | 5.4901 | 6.0836 | 149 | | 5.4877 | 5.9086 | 150 | | 5.4842 | 5.8724 | 151 | | 5.5167 | 5.7298 | 152 | | 5.5043 | 5.7802 | 153 | | 5.4737 | 6.0805 | 154 | | 5.4805 | 6.0888 | 155 | | 5.4765 | 5.9967 | 156 | | 5.4691 | 5.9332 | 157 | | 5.4697 | 6.0675 | 158 | | 5.4648 | 6.0689 | 159 | | 5.4658 | 5.9954 | 160 | | 5.4721 | 5.8917 | 161 | | 5.4641 | 5.8973 | 162 | | 5.4703 | 6.0126 | 163 | | 5.4753 | 5.9064 | 164 | | 5.4731 | 6.0835 | 165 | | 5.5094 | 5.5720 | 166 | | 5.5355 | 5.9077 | 167 | | 5.4791 | 6.0669 | 168 | | 5.4690 | 6.0729 | 169 | | 5.4635 | 5.9580 | 170 | | 5.4698 | 6.1453 | 171 | | 5.4668 | 5.9952 | 172 | | 5.4728 | 6.0041 | 173 | | 5.5062 | 6.1592 | 174 | | 5.4944 | 5.9536 | 175 | | 5.4802 | 5.9673 | 176 | | 5.4710 | 5.9888 | 177 | | 5.4653 | 6.0656 | 178 | | 5.4618 | 6.0278 | 179 | | 5.4659 | 5.9563 | 180 | | 5.4596 | 6.0022 | 181 | | 5.4627 | 5.9594 | 182 | | 5.4688 | 5.8462 | 183 | | 5.4662 | 5.9550 | 184 | | 5.4646 | 5.9757 | 185 | | 5.4753 | 5.9400 | 186 | | 5.4911 | 5.7438 | 187 | | 5.4681 | 6.0941 | 188 | | 5.4719 | 6.0324 | 189 | | 5.4692 | 6.0313 | 190 | | 5.4634 | 5.9874 | 191 | | 5.4639 | 5.9928 | 192 | | 5.4714 | 6.0265 | 193 | | 5.4569 | 5.8387 | 194 | | 5.4606 | 6.0462 | 195 | | 5.4667 | 5.9636 | 196 | | 5.4653 | 6.0299 | 197 | | 5.4623 | 6.0311 | 198 | | 5.4629 | 5.9745 | 199 | | 5.4630 | 5.9398 | 200 | | 5.4618 | 5.9005 | 201 | | 5.4611 | 5.8718 | 202 | | 5.4979 | 5.7893 | 203 | | 5.4995 | 5.8556 | 204 | | 5.4949 | 5.9533 | 205 | | 5.4806 | 6.0033 | 206 | | 5.4700 | 6.0395 | 207 | | 5.4601 | 6.0592 | 208 | | 5.4605 | 6.1408 | 209 | | 5.4638 | 6.0469 | 210 | | 5.4592 | 6.1216 | 211 | | 5.4646 | 6.0284 | 212 | | 5.4607 | 5.8940 | 213 | | 5.4573 | 5.8946 | 214 | | 5.4690 | 5.8057 | 215 | | 5.5077 | 5.8491 | 216 | | 5.4734 | 5.9847 | 217 | | 5.4859 | 5.9075 | 218 | | 5.4889 | 6.0483 | 219 | | 5.4837 | 6.0959 | 220 | | 5.4878 | 5.9962 | 221 | | 5.4854 | 5.9575 | 222 | | 5.4763 | 6.0648 | 223 | | 5.4890 | 5.9731 | 224 | | 5.4866 | 5.9771 | 225 | | 5.4906 | 5.8407 | 226 | | 5.4735 | 5.9678 | 227 | | 5.4777 | 5.9756 | 228 | | 5.4718 | 6.2007 | 229 | | 5.5181 | 6.2549 | 230 | | 5.4902 | 5.9385 | 231 | | 5.4804 | 5.8927 | 232 | | 5.4670 | 5.9336 | 233 | | 5.4641 | 6.0430 | 234 | | 5.4797 | 5.9510 | 235 | ### Framework versions - Transformers 4.40.2 - TensorFlow 2.15.0 - Datasets 2.19.1 - Tokenizers 0.19.1